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3 Software Tools for a Remote First Working Culture

During the lockdowns in the US and India due to the Covid-19 pandemic, our employees across all our delivery centers in the US and India had to start working from home. At Value Global we strive to be a business strategy partner that provides IT Optimization services onsite and remotely. 

While Value Global has always provided clients with the option of having a remote working team, it became imperative that we move to a 100% remote first working culture so that our client service levels continue to remain the same as before Covid-19. 

In this article, we share our experience of transitioning from a Work Office Culture to a Remote First Culture.  We hope that by sharing our experience we help you make better decisions and get an idea of the Do’s and Don’ts of moving to a Remote First Culture.

Getting Work Done and Keeping Employees Happy!

For us as a company, we are very concerned about keeping employee engagement high as it is directly correlated to both employee productivity and customer success.  Commute times to and from office are certainly a big factor for every employee that works in large cities such as Houston and Chennai.  Our challenge though was manyfold – how to keep employee morale high, how to keep them interested, how to help them collaborate and how to continue to have our team leads engage and mentor their teams and maintain service levels for their customers.   

We decided that we will need to engage the team leads to effectively guide, mentor and communicate with their team members as they would have done in an office setting.  The remote first does not necessarily change the structure that we had put in place which worked perfectly. It however required fine tuning of the processes to ensure the same level of effectiveness. 

Preparing for a Remote First Work Culture.

The big question for us then became: Are We Ready to Work from home?

For the management, there were four major areas where we had to be ready. Our systems had to be ready to support our employees. All processes should be in place for the smooth flow of communication. In addition, the delivery of solutions and services need to happen in a secure environment. 

People Readiness – Many of our employees were not new to working from home but they did it in exceptional circumstances.  Since we are planning to transform ourselves into a Remote First culture, we knew it was important to understand the concerns of the people in our organization. We started sessions where our  HR and Operations team worked together with the employees to understand their concerns and ability to gear up to a remote first culture.

Process Readiness – We have tools such as G Suite for Business, Zoom and Google Hangouts  which many of our employees have used in the past. However, we have started training employees on the same considering not everyone is used to Asynchronous communication.  We started instituting processes on usage of these toolsets to optimally support delivery of our services. . In addition, we also revised some job descriptions and KPIs for our employees considering the changed situation.

Security Readiness – Security on infrastructure used by the team needed to be validated to ensure that security patches and antivirus/malware softwares are up to date.  Our cybersecurity preparedness already includes a secure communication/VPN and file sharing platform which secures the client environments and data being supported by our employees. 

System Readiness – Being a cloud first company, our existing infrastructure was already being supported in a hybrid cloud model which allowed us to transition seamlessly to a Remote First model. It has become important to build additional stand-bys and redundancies for the technical infrastructure used for supporting customers from homes. The operational processes needed to be put in place to support this level of redundancy.

At the same time we needed the software tools to help our projects move smoothly.  Here are three software communication tools that became the foundation of our transition:

1. G Suite Business Solutions – Google

Google Drive

At Value Global, we extensively use G Suite of products starting with Google Drive for storage of documents and project files.  Google Drive is a cloud-based storage solution that allows you to keep your project files in one centralized location. Anyone in your team can upload files, create directories, and share these with other team members who might need them for their own set of tasks.

Google Drive comes with a powerful set of office tools that let you create and edit documents, spreadsheets, and slides. You can track the edits made by team members in real-time, accept and reject suggestions, and tag people in comments and notes.  This feature becomes super useful where the documents can be worked on asynchronously by team members.

Gmail and Google Calendar

Gmail is our go to tool for email communication.  From scheduling our meetings and other deadlines our company practice is to share Google Calendar with our colleagues. The privacy settings allow our employees to choose who they want to share the schedule with.

Google Calendar also allows us to add notes in the description to elaborate the agenda of the meeting.  For e.g. “I’d like to book this meeting to discuss the marketing newsletter. Let me know if this time doesn’t work for you.” 

Google Hangouts

Another Popular software for virtual meetings and conferences at Value Global is Google Hangouts.  One can join a meeting on Google Hangouts directly from Google Calendar. Not only that it makes it easy for users to share their screen for enabling quick troubleshooting.  We also use Google Hangouts to make phone calls, initially the call quality was not that great but over the last year the call quality has certainly gotten better. Video conferencing through Hangouts is an amazing tool, after all a picture is worth a thousand words :-). 

2. Zoom

For communicating with Clients, we use Zoom.  Zoom is another easy-to-use, popular video conference software available on desktop and mobile app that allows us to schedule, launch, and record virtual meetings.  Clients can join meetings through a computer, smartphone, or by voice via a dial in phone. During Zoom meetings, we can also share our screen with clients so they can see our work or presentations.

3. WhatsApp

A popular chatting platform WhatsApp allows group calls to have small meetings. The software is also available on desktop. We predominantly use it for quick communication. One of the problems we are anticipating with Remote First is employees feeling lonely or socially detached when working from home or any remote location as opposed to working from the office. That is why we have also started creating separate interest groups such as knowledge sharing, healthy lifestyle, and current events for our employees where they can chat about topics other than those related to work. Our customers also find that they can connect and work with our teams through the chat platforms. 

Employees are our biggest assets and at a time when they are extremely concerned about their own and their family’s health, the decision to allow them to work from home was an immediate decision for us.  We know that happy and healthy employees deliver excellent results and we will make every decision to make them happy, healthy and safe. We know many companies are contemplating moving to a work from home policy and shrinking their overall spend on the office infrastructure.  Has your company moved to Remote First yet? If yes, we are eager to know the tools that helped you transition and the challenges you face. 

“Value Global is a Houston, TX based company with technology and remote support centers in India.  We provide Application and Infrastructure Managed Services to Global Fortune 500 customers. Our mission is to provide agile, scalable, and cost-effective information technology solutions that drive your business forward.”

About the Author: Kumar Nadar is the Managing Partner at Value Global, a leading managed services provider to Fortune 500 Companies.

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How Can Retailers Harness Big Data?

Big data analytics are becoming increasingly indispensable across most industries, including retail. When retailers clearly understand their industry by leveraging key information, they can improve their marketing efforts, demand forecasting, inventory planning, and much more. However, those looking to big data for improvements must overcome certain challenges and develop specific strategies before implementing big data analytics into their businesses. With a range of potential opportunities, what are some business applications for big data in the retail sector?

What are retailers doing?

Retailers can leverage big data in several ways to gain an edge. Here are five key areas worth mentioning:

  1. Personalization — Many retailer websites feature recommendation engines that use customer preferences to tailor selection results. However, it can be challenging for these engines to make recommendations effectively without being obtrusive. For instance, generating irrelevant offers can irritate potential customers. Through big data analysis and machine-learning capabilities, retailers can use customer information to train their engines. For example, they can improve relevance by implementing a control loop that compares generated recommendations to response rates. In other words, retailers are using big data to improve personalization with increasing accuracy.
  2. Pricing — Product prices can fluctuate throughout the year, especially during high-demand periods. How do retailers adapt? Through big data analytics, retailers can employ dynamic pricing, a pricing method that automatically adjusts their prices in response to their competitors’. Retailers can use analytics software that monitors prices and creates rules so the software adjusts prices accordingly. However, if retailers don’t check or limit their dynamic pricing controls, they can become problematic; if a competitor drastically discounts a product and the retailer hasn’t set restrictions on his or her dynamic pricing system, it can devastate margins. Therefore, big data has the capacity to make real-time price matching easy and effective — but only if retailers set clear boundaries.

  3. Inventory — It’s important for any retailer to have a clear view of his or her inventory, especially if he or she oversees more than one location or channel. In the past, industry insiders relied on physical observations and manual inventorying. Now, a variety of digital touch points makes inventory management simpler, even for those with multiple channels. Big data analytics can help retailers track their inventories and understand trends, which, in turn, can help them better — and more accurately — prepare for changes in demand.
  4. Competition — As with inventory, previous competitor assessment methods were relatively low-tech. Retailers can do more than set competitor pricing alternatives based on real-time data: They can also use competitors’ success to their own advantages by monitoring which competing deals are the most profitable and localizing prices based on what competitors’ customers are buying.
  5. Sensor analytics — Through increasing Internet of Things (IoT) connectivity, retailers have more opportunities than ever to connect with and attract customers. This year, more retail owners will likely “profit from an increase in sensors and data coming from various customer-owned devices.” This, in turn, is generating greater interest among global retailers hoping to take advantage as 70% are “ready to adopt the Internet of Things to improve customer experiences.” By leveraging customer information on everything from loyalty cards to social media platforms and store apps, retailers can use these countless data points to gain an edge.

It’s clear that, when it comes to harnessing big data, there’s plenty of room for retail success. To truly unlock big data’s potential, retailers will likely invest in more IoT, machine learning, and automation technology. However, careful strategic planning and preparation are essential for any business leader planning to tap into big data. Retail executives should understand what their goals are for leveraging big data, what information they will need, and how they will turn insights into actions moving forward. Without proper planning, it is easy to become overwhelmed — and more information can hinder rather than help business operations. Data has always driven decisions: Big data technology is exciting because it drives smarter, faster, more accurate decisions based on real-time information from many, many data points.

The experts at Value Global understand the retail landscape and offer many customized IT solutions. If you’re looking to leverage smarter ways of doing better business, visit Value Global online or give us a call at 281.713.9895.

Migration Strategies within Enterprise Platforms

Behind any successful IT organization lies a network of well-functioning and up-to-date enterprise applications. One challenge many business leaders face is managing an effective data migration strategy. Moving application data from one version or platform to another can be a risky and extensive process with significant consequences if not executed properly.

Migration challenges

According to one senior applications analyst, despite high data migration costs, about 75% of systems fail to meet expectations. This failure is due to migration process flaws, preventing many company leaders from delivering the competitive advantages they desire. According to the Oracle whitepaper, analysts can organize common data migration challenges and risks into four areas: effort, expertise, data quality, and migration strategies or methods.

More specifically, three primary challenges exist for migrating data within enterprise platforms. First, company leaders experience migration downtime. Second, many tech leaders are still making manual changes to critical apps to support their development life cycles. However, it’s best to automate all changes with minimal manual intervention. Third, all changes need to be auditable due to financial loss and compliance cost risks. It’s imperative to understand the technical steps necessary for successfully moving from one system to another.

Migration steps and benefits

Fortunately, enterprise platforms provide a range of migrating and reporting tools that can expedite the migration process, allowing company leaders to go live within days or weeks instead of months or years. But how can IT professionals best utilize these tools to design safe and efficient data migration processes? The key steps to this process are:

  1. Determine which data IT experts require for the migration process. To map out the data you’ll need to migrate to your new system, it’s crucial you have a good understanding of the application data relevant to your business process.
  2. Leverage available application program interfaces (APIs). Many enterprise platforms have data integration points and well-defined interfaces to facilitate data migration. These will help validate and load the data into the source or target system.
  3. Develop conversion design and data mapping. Data conversion design is crucial in this process, as it involves extracting data from the legacy system, utilizing templates to load data, preparing a mapping sheet to map the source data to the target data, and converting the data if required during mapping and validation.
  4. Finalize data for migration. IT experts must review every aspect of migrated data to ensure it will properly convert into target systems’ required forms.
  5. Load data into a test instance for quality assurance. This step can help catch any lingering issues or deficiencies in your data and provides a more detailed quality analysis prior to final upload.
  6. Implement data migration. This is a straightforward step but can be time-consuming depending on how much data you’re migrating.
  7. Perform final validation prior to production. Since detailed validation occurred in previous steps, this final validation should provide only high-level data.

Though these steps may seem straightforward and simple, each comes with its own set of challenges. An enterprise system’s integrity can impact business operations and profitability. Therefore, it may be prudent to hire an enterprise data migration services expert who understands complexities inherent to managing ever-changing technologies and can help oversee the migration process.

When done right, data migration can present you with significant business benefits, including:

  • Greater business goal achievement via new infrastructure adoption
  • Improved business performance and continuity
  • New functionality, thanks to migration to a more up-to-date platform
  • Reduced complexity and improved data consolidation
  • Improved supportability and serviceability
  • Lower support costs

Of course, no data migration process is one size fits all, and how you migrate data from legacy systems to newer, faster, more efficient ones may depend on your particular circumstances. However, by understanding what data migration entails and carefully following safe migration steps, you can improve corporate performance and deliver a competitive advantage for your clients.

At Value Global, our expert team members are seasoned in Oracle EBS solutions and processes. We understand complex data migration and can help you achieve desired results. Contact us to discover how a partnership can help your IT infrastructure — and your business — operate with excellence.

Descriptive or Predictive? How to Evaluate Your Data Maturity

How are advances such as artificial intelligence, machine learning, and big data shaking up the ways tech leaders do business? Technology disruptions are progressing at a rapid pace and will likely continue in years to come. But what are these advances, really, and how can professionals harness them for the good of their businesses? As they dive deeper into their big data, how can company leaders better position themselves for information and analytics?

Evaluating data maturity

The first step is assessing your analytics environment using a Data Analytics Maturity Model. The Maturity Model is a guide designed to help organizational leaders understand where they stand with respect to achieving intelligence from their data. Using the Data Analytics Maturity Model to assess current and necessary future business tools, tactics, and technologies can help business leaders create paths forward for successfully implementing and utilizing information analytics.

At the core of any Data Analytics Maturity Model is a visual tool for better understanding which types of analytics fall under the information analytics umbrella. Although descriptive and diagnostic analytics can and do provide useful information such as what happened and why, predictive and prescriptive analytics offer insights into what will happen and how business leaders can better plan for the future. By asking the right actionable questions about problem prevention and elimination, business professionals can develop strategies that could make information analytics an invaluable tool for competitive advantages.

Traditionally designed around five dimensions, this analytic model includes five stages of maturity. A Transforming Data With Intelligence (TDWI) assessment describes the five categories.

  1. Organization If at all, how much does your business support an information analytics program? Do you have enough organization within your company to successfully employ information analytics, or do you need to do more work?
  2. Infrastructure How advanced and coherent is the architecture supporting your information analytics initiatives? What supportive structures do you have in place, and how did you integrate them into the existing environment?
  3. Data management How extensive is your data volume, variety, veracity, and velocity, including data quality and processing?
  4. Analytics How advanced are you and fellow company leaders in analytical use? Are you taking predictive or prescriptive approaches yet?
  5. Governance How coherent is your company data governance strategy?

By assessing company strengths in each of these fields, leaders can determine how prepared their companies are to utilize information analytics.

From descriptive to predictive

Analysts assess company data maturity in stages — described by its organizational leaders’ experience with and dedication to using information analytics. Those in pre-adoption companies have little existing support for big data or are only beginning to invest in or research big data utilization. Early adopters, on the other hand, have dedicated teams for information analytics and even proofs of concept, depending on the team experience. Corporate adopters and leaders in mature companies have fully adopted and invested in big data, using prescriptive analytics for optimal decision-making. Those with full maturity are using big data to transform the ways in which they operate their businesses, using smart data in a variety of disruptive ways.

Business decision-makers who haven’t yet integrated information analytics into their businesses — those “pre-chasm” companies — may take preliminary steps to identify actionable problems and assess data capabilities. However, their maturity will restrict them to descriptive and diagnostic analytical tools. Of course, it would be problematic for those at this stage to attempt a leap to full maturity; a gradual approach is best for most. Fully mature companies such as Facebook and Amazon have arsenals dedicated to optimizing big data and often feature company cultures built around innovation that took years to cultivate.

At mature companies, leaders use information as a strategic asset and data drives continuous innovation. Business leaders implement machine learning and automation to streamline operations and they also embrace cultures of investigative insight that put new ideas into action. This imbibes a scientific decision-making process instead of an artistic one.

The maturing process requires company leaders to align business strategies with technical strategies, action-based problem solving, and customized road map development.

Advancements in information analytics are constantly evolving, and it can be difficult to keep up. If you’re not sure where to start or which stage in your maturity comes next, it could be time to partner with an expert who can guide you to analytics maturity. Contact the professionals at Value Global to get your assessment done.

Transform Your DevOps: Go Digital

The cloud revolution has reshaped the way we function as business professionals, improving efficiencies and streamlining processes. As this technology continues proving its worth, more decision-makers are utilizing — and embracing — cloud implementation. In fact, according to a 2017 CommVault report, 56% of IT teams surveyed “have moved or intend to move all of their processes to the cloud.” A key but often overlooked element of this cloud revolution is cloud technology’s effect on existing DevOps culture.

Modern-day DevOps

In recent years, DevOps has expanded from its roots as “just a set of tools” to include models such as infrastructure (IaaS) and platform as a service (PaaS). Although the definition of DevOps remains up for debate, it’s best described in this context as a means of facilitating software development with a focus on processes and user experiences (UX). For many, DevOps now encompasses app and resource management, scalability, and security, among other benefits. And cloud-centric DevOps includes even more capabilities.

Interactions between DevOps and cloud technology, or CloudOps, can better streamline certain operations such as product development and testing. For IT professionals, especially those involved in DevOps, this can mean

  • improving UX,
  • increasing automation, and
  • decreasing costs.

Therefore, understanding cloud-centric DevOps and how to best implement it is very important.

Implementing cloud-centric DevOps

Automation is key for implementing cloud-centric DevOps. Successful implementation also entails optimizing cloud infrastructure and automating other particularly time-consuming processes. As you migrate more data, services, and applications to the cloud, operational concerns — such as minor bugs and human errors — can become less obstructive.

Despite the emergent nature of cloud-centric DevOps, there are already many implementation best practices standards in place:

  • Train employees in both DevOps and cloud technology, and allocate resources responsibly between both areas.
  • Remain flexible by utilizing DevOps tools compatible with multiple cloud platforms.
  • Structure cloud services in a way that allows for application and service modularity.
  • Ensure proper security measures and governance, and remember that risk mitigation is an ongoing process.
  • Automate where possible, including security checks and testing processes.

Many cloud service functions, such as automation, allow developers to maintain better control over their projects down to each component, improving productivity and reducing human error. Streamlining processes altered by cloud-centric DevOps can reduce downtime and increase reliability, providing a better overall UX.

It’s no secret the relationship between cloud technology and DevOps can be difficult to decode at times. However, with just a little preparation and due diligence, IT professionals in every role, especially development and operations, may see long-lasting benefits.

The cloud revolution and DevOps are both reshaping how IT businesses function. In a changing world, you need world-class IT solutions. That’s where Value Global comes in. Visit us online to learn more.

What Top 2018 Tech Trends Could Impact Your Business?

We’ve hardly scratched the surface of 2018, but it’s never too early to anticipate and prepare for technology trends and developments promising to shape the future of managed services — and the world. Although many of these developments pose beneficial opportunities for tech company leaders, they may also present challenges to those not ready for impending industry changes.

Here are the biggest trends of 2018 you need to know about and how they may impact your business.

Artificial intelligence and machine learning

It’s no secret implementing smarter, faster programs into company workflows can offer sweeping benefits. From accurate, adaptable analytics to automation and beyond, some major disruptive developments entail artificial intelligence (AI) and machine learning. Gartner researchers predict having the ability to use AI will “reinvent business models” and user experiences over the next several years. Although virtual assistants like Alexa are mainstreaming AI, experts agree the greatest changes will occur through implementing narrow AI, which utilizes machine learning to fulfill specific, data-intensive tasks. For companies whose leaders utilize this technology, this means advances in predictive decision-making and augmented analytics, which use machine learning to prepare data and discover deep insights for a wide range of solutions.

Smart devices and the Internet of Things (IoT)


As with AI, advances in IoT applications promise to revolutionize analytics and networking. By increasingly and constantly connecting billions of IoT devices, business insiders are making leaps in data management and service automation. Perhaps more important, the amount of information and speed of analysis IoT offers is enabling many business professionals to work more efficiently and profitably than before. For example, truck manufacturers reduced their 180,000-truck fleet management costs by 80% thanks to versatile datasets they created using connected technology. IoT implementation benefits have prompted many industry power players, such as those at Microsoft, to invest heavily in IoT analytics, and savvy tech leaders are following suit.

Augmented world

augmented reality

It has become exceedingly clear in the last few years that virtual reality is useful for more than just video games. The technology underlying immersive digital worlds has disrupted many areas from user experiences to assistive technologies. Many major developments in augmented reality (AR), which provides visual overlays on physical objects, are proving their worth in the business arena. Gartner researchers predict that “mixed reality,” a technology that combines digital and real-world objects to create a virtual user experience while keeping users rooted in the present, is a key aspect of AR worth watching over the next five years.

Another AR-adjacent trend is the continued development of conversational platforms. Thanks to advances in AI and machine learning as well as AR, some company leaders have turned to chatbots for automating and streamlining their customer service interactions. Early conversational technology implementations were limited to highly structured, simplistic answers. However, according to the Gartner article, these platforms will likely evolve in the coming years as they become able to incorporate complex vocal and even visual data to complete user requests. More robust conversational technology stands to benefit those whose jobs span multiple industries by delivering advanced user-friendly interactive experiences.

Cloud services

Cloud services are becoming an obvious choice for many company leaders looking to streamline business operations. As a result, more and more business decision-makers are turning to MSPs, helping them to better understand, implement, and manage their cloud-based services with the added benefit of ongoing support. As a means to save costs, using public clouds is also becoming a go-to option for many. This, in turn, is driving an even greater demand for hybrid clouds. And as more business professionals better understand hybrid cloud advantages, flexibility, and value, many dub 2018 the “year of the hybrid cloud.” Based on increasing successes and demand, it’s likely cloud platforms will remain a force used for consolidating or eliminating antiquated on-premises business systems.

2018 should be an exciting year as many business processes are ripe for disruption as more and more company leaders recognize the benefits behind these technologies. Many are shifting their mindsets from the notion that these are simply buzzwords to understanding, realizing, and utilizing their value. Smart company leaders are already taking steps to corner these emerging technologies, working to innovate and increase value for their customers.

For more on the latest trends and developments shaping managed services and disrupting businesses, or to learn more about innovative managed services solutions, visit Value Global online.
Double exposure of women Engineer in hipster shirt working with tablet in control room of oil and gas platform or plant industrial for monitor process, business and industry concept
Information Technology, Technology

Automated, Accelerated, Applied: How Machine Learning Can Improve Your Managed Services

For any company that relies on managed service providers (MSPs) to automate IT services and streamline operations, there are no two words perhaps more important to their future than machine learning. Machine Learning is the intelligent interpretation of high volumes of data by machines to make improvements without being explicitly programmed.

Although machine learning is not a new concept to data scientists, the term has taken the business world by storm in the last several years, thanks to its increasingly wide range of applications. In fact, a Forrester brief states that machine learning investments should increase by more than 300% this year compared to 2016. As machine learning becomes more common for MSPs and used within more applications, it will become more fundamental to the success of any emerging business.

Traditionally, managed services collect large volumes of data from their monitoring services. The data is collected, reviewed, and acted upon by the service provider. As the volume of data scales up, it becomes increasingly challenging, if not impossible, to have eyes reviewing all the data being generated. This is where automated workflows can be highly effective in improving existing managed service solutions. Those quick to adapt are already seeing that machine learning serves to accelerate these improvements — but how?

Machine learning 101

Brain with printed circuit board (PCB) design and businessman representing artificial intelligence (AI), data mining, machine learning and another modern computer technologies concepts.

Like other innovations, such as the computer and the steam engine, machine learning is known as a foundational technology — that is, one whose applications grow both horizontally and vertically beyond its initial intended use. As the Entrepreneur article points out, those applications include self-driving cars, music recommendations, and personalized ads.

Some of these processes may seem like the work of pure magic; however, in reality, they’re  highly advanced and complex. This technology operates via a facet called deep learning. In short, a computer uses unstructured data — such as pictures, sounds, and behaviors — and draws conclusions based on rules of its own design. This differs from the logic found in traditional programs in that a machine learning program operates autonomously and intuitively.

virtual human Machine learning helps to quickly analyze the data and then recommends a set of actions. For example, existing data collected from monitoring is analyzed for trends, patterns, or issues previously faced to identify actions that can be implemented. The ability to use existing customer data to generate a prediction model and identify an optimal algorithm can, in turn, improve a MSP user’s ability to locate and attract new customers. Where users once had to sift through millions of rows the algorithm goes through based on patterns and shortlist data elements, they can now look at a very rapid pace and drive actions.

Currently, most MSPs use automated workflows that they create themselves and program into the systems, but machine learning would eliminate the need for a person to do that. Thus, this high-performing interpretation helps to automate IT operations on a greater scale than ever before.

Smarter data integrity

Server racks in server room data center. 3d render

Forward-thinking and the adaptation of such technologies is important to both MSPs and their clients. Incorporating a more advanced level of predictive analysis and automation can enhance proactive monitoring and reduce the level of effort required of consultants. While MSPs help to streamline a business through managing IT complexities, machine learning optimizes the functions of these complex systems, creating a win-win.

For Value Global clients, machine learning means improved data analytics, which translate to better levels of service and a more efficient organization. The intricate data sets these systems build ultimately allow users to gain new insights and improve existing services. And the ability to fast-track the evolution of managed services can save both time and money, while also giving users a competitive advantage.

As machine learning becomes more common in technology and, more importantly, in business, clients will continue to demand more intensive and intelligent IT services. Thankfully, the organic, foundational nature of machine learning offers an optimistic image for the future of managed services. All it takes is the desire to innovate — and a little clever programming.

When it comes to managed services and intelligent IT solutions, Value Global is committed to innovation. Contact us for more information about machine learning, or visit us online to learn more about our great services.
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